In this chapter, the foundations of the machine learning process will be described in detail. Supervised and unsupervised machine learning will be explored further. Some of the most commonly used machine learning models and algorithms will be described in detail. This includes dimensionality reduction. The chapter will also look at some of the things to keep in mind during the feature engineering stage. It also talks about model fitting, specifically, overfitting and underfitting and how to avoid them.
© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2022
M. SekarMachine Learning for Auditorshttps://doi.org/10.1007/978-1-4842-8051-5_99. Machine Learning Fundamentals
Maris Sekar1
(1)
Calgary, AB, Canada
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